Device measures fluid drag on test vehicles

Electromechanical drag balance device measures the aerodynamic drag force acting on a vehicle as it moves through the atmosphere and telemeters the data to a remote receiving station. This device is also used for testing the hydrodynamic drag characteristics of underwater vehicles

Air frame drag balance Patent

Device for measuring drag forces in flight test

Information Sources and Purchase Influences For Wood Products Retailers: A Trade Show Attendee Perspective

Retail outlets are an important channel of distribution for wood products sold to professional builders and do-it-yourself consumers. Trade shows serve a prominent role in the wood products industry as a means for showcasing wood building products to such retail outlets. This research provides information about the use of trade shows by building material retailers that will allow wood marketers to better target marketing programs. A survey of all retailer attendees at a large building materials trade show was conducted to determine which information sources are most influential in retailers' purchase decision-making. The survey also investigated which at-show information sources are most influential for buyer-attendees. Results indicate that retailers' relationship with their wood products supplier has the greatest influence on overall purchase decisions. Price reductions on materials displayed at the show was the most influential show-related factor. Statistical analyses suggest that in-exhibit information sources are more heavily used by attendees with greater purchase influence. Additional analyses indicate that attendees with greater purchase influence tend to seek technically oriented information about products displayed

Industrial effluent treatment with immersed MBRs: Treatability and cost

A comprehensive OPEX analysis for both municipal and industrial wastewaters has been conducted encompassing energy, critical component (membrane) replacement, chemicals consumption, waste disposal and labour. The analysis was preceded by a review of recent data on industrial effluent treatability with reference to published chemical oxygen demand (COD) removal data for four effluent types: food and beverage, textile, petroleum and landfill leachate. Outcomes revealed labour costs to be the most significant of those considered, contributing 50% of the OPEX for a 10,000 m3/day capacity municipal wastewater treatment works. An analysis of the OPEX sensitivity to 12 individual parameters (labour cost, flux, electrical energy cost, membrane life, feed COD, membrane cost, membrane air-scour rate, chemicals cost, waste disposal cost, mixed liquor suspended solids (MLSS) concentration, recirculation ratio, and transmembrane pressure) revealed OPEX to be most sensitive to labour effort and/or costs for all scenarios considered other than a large (100,000 m3/day capacity) works, for which flux and electrical energy costs were found to be slightly more influential. It was concluded that for small- to medium-sized plants cost savings are best made through improving the robustness of plants to limit manual intervention necessitated by unforeseen events, such as electrical/mechanical failure, foaming or sludging. - IWA Publishing 2019.This work was made possible by the support of a National Priorities Research Programme (NPRP) grant from the Qatar National Research Fund (QNRF), grant reference number NPRP8-1115-2-473. The statements made herein are solely the responsibility of the authors

Detecting periodicity in experimental data using linear modeling techniques

Fourier spectral estimates and, to a lesser extent, the autocorrelation function are the primary tools to detect periodicities in experimental data in the physical and biological sciences. We propose a new method which is more reliable than traditional techniques, and is able to make clear identification of periodic behavior when traditional techniques do not. This technique is based on an information theoretic reduction of linear (autoregressive) models so that only the essential features of an autoregressive model are retained. These models we call reduced autoregressive models (RARM). The essential features of reduced autoregressive models include any periodicity present in the data. We provide theoretical and numerical evidence from both experimental and artificial data, to demonstrate that this technique will reliably detect periodicities if and only if they are present in the data. There are strong information theoretic arguments to support the statement that RARM detects periodicities if they are present. Surrogate data techniques are used to ensure the converse. Furthermore, our calculations demonstrate that RARM is more robust, more accurate, and more sensitive, than traditional spectral techniques.Comment: 10 pages (revtex) and 6 figures. To appear in Phys Rev E. Modified styl